Automatically deriving the quality of a Spoken Dialogue System is an important task for both assessing dialogue systems and improving them. Work on automatic quality estimation for each system-user-exchange further holds the opportunity of using this quality information for online-adaption of the dialogues. The Interaction Quality paradigm is the first metric holding those features. Hence, this contribution gives an overview over the Interaction Quality paradigm and reviews recent estimation approaches. Furthermore, it renders drawbacks of the current approaches and proposes further directions in order to improve the estimation accuracy.
free text keywords: РЕЧЕВАЯ ДИАЛОГОВАЯ СИСТЕМА, ОЦЕНКА ДИАЛОГА, МАШИННОЕ ОБУЧЕНИЕ